Wireless Sensor Networks (WSNs) comprise a number of sensor nodes which typically sense, measure and report environmental data. The nodes themselves are highly resource constrained. They are typically networked in a self-organising manner without any specific infrastructure or centralised control. The key objective of WSN protocols is to minimise the cost of ambient data collection. Ambient data samples need to be collected and forwarded through minimum cost links (in terms of hop count and consumed energy) to data consumer access point (sink) for further analysis and manipulation.WSN routing is the field of research that focuses on the interconnection of sensor nodes via either single or multi-hop paths to forward data packets from event regions to the sink. However, the routing overhead increases if raw data packets are forwarded from each source region to the sink. Data aggregation is therefore a technique that has the potential to collect and combine data packets to express the collected information in a summary form. It reduces the number and size of transmissions and eliminates redundant data packets. WSN Routing can be performed in two models for data aggregation: mobile agent and client/server. The former routes mobile agent(s) to collect and aggregate data samples from the sensor nodes, whereas the latter establishes an hierarchical network in which data packets are aggregated and forwarded from the ambient event regions to the sink in a convergent manner.Data aggregation routing aims to maximise the number of collected data samples, while minimising energy consumption and data collection delay. Minimising energy consumption is a vital requirement due to resource constraints in WSNs. Data collection delay should be minimised as it is the key to data freshness. At the same time, the number of collected data samples should be maximised, as it should lead to increased accuracy and robustness in data collection.To achieve the objectives of data aggregation routing, this thesis proposes two data aggregation protocols: one for mobile agents (called ZMA) and another using client/server (named CBA). ZMA uses multiple mobile agents to collect and aggregate over a WSN. The mobile agents start their journeys in a bottom-up manner from the event regions to the sink. They visit the sensor nodes and collect and aggregate data samples and then return to the sink to deliver the (aggregated) results. CBA partitions the network into a set of data-centric clusters and then establishes a spanning tree from the cluster-heads to the sink to forward and aggregate data packets hierarchically.The performance of the proposed protocols is tested and evaluated through simulation. The simulation results of each of the proposed protocols are compared against two well-known protocols for each routing model, namely TBID (Tree-Based Itinerary Design) and NOID (The Near-Optimal Itinerary Design algorithm) for mobile agents and LEACH (Low-Energy Adaptive Clustering Hierarchy) and DDiFF (Directed Diffusion) for client/server. The results indicate that the proposed algorithms perform well compared to the respective benchmark protocols in most circumstances.
|Date of Award||1 Oct 2014|
|Supervisor||Julian Padget (Supervisor) & Marina De Vos (Supervisor)|